Is the Food and Nutrition Board’s recommended daily allowance for vitamin D flawed?

In 2011 the Food and Nutrition Board (FNB) may have used flawed statistics to recommend a RDA for vitamin D of 600 IU/day for most adults.

The FNB’s statistical analysis showed that 600 IU/day of vitamin D would get 97.5% of the population above 20 ng/ml. They based their recommendations on 10 different supplementation studies that used a total of 32 different doses.

Now two statisticians from the University of Alberta write that the FNB’s statistics were flawed and 600 IU/day will get 97.5% of the population only above 11 ng/ml.

In fact, their analysis of those ten studies showed that 8,895 IU/day are needed to get 97.5% of the population above 20 ng/ml.

The author’s technique was as follows:

“We used 8 studies (using a total of 23 different doses) that had dose response as well as standard deviation and for each of these 23 study dose averages we calculated the 2.5th percentile by subtracting 2 standard deviations from the average. Next, we regressed these 23 values against vitamin D intake to yield the lower prediction limit. This regression line revealed that 600 IU of vitamin D per day achieves that 97.5% of individuals will have serum 25(OH)D values above 26.8 (11 ng/ml) nmol/L rather than above 50 nmol/L (20 ng/ml), which is currently assumed. It also estimated that 8895 IU of vitamin D per day may be needed to accomplish that 97.5% of individuals achieve serum 25(OH)D values of 50 nmol/L or more.”

The authors state:

“The public health and clinical implications of the miscalculated RDA for vitamin D are serious. We recommend that the RDA for vitamin D be reconsidered to allow for appropriate public health and clinical decision-making.”

If their statistics are correct – and I’m not a statistician – I’d say this is a serious error. It is what we call an order of magnitude error, which is a ten-fold error.

1 Response to Is the Food and Nutrition Board’s recommended daily allowance for vitamin D flawed?

Yes, statistical calculations often remove outliers (data which does not conform)
Outliers are sometimes considered to be that which is beyond 2 standard deviations,
This study, however, SUBTRACTS 2 standard deviations from ALL of the data
Have never seen that done before.
Seems totally invalid.